Jake Grigsby

According to our database, Jake Grigsby authored at least 16 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback.

Thai Hoang, Kung-Hsiang Huang, Shirley Kokane, Jianguo Zhang, Zuxin Liu, Ming Zhu, Jake Grigsby, Tian Lan, Michael S. Ryoo, Chien-Sheng Wu, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong, Juan Carlos Niebles

CoRR, June, 2025

VLM Q-Learning: Aligning Vision-Language Models for Interactive Decision-Making.

Jake Grigsby, Yuke Zhu, Michael S. Ryoo, Juan Carlos Niebles

CoRR, May, 2025

Human-Level Competitive Pokémon via Scalable Offline Reinforcement Learning with Transformers.

Jake Grigsby, Yuqi Xie, Justin Sasek, Steven Zheng, Yuke Zhu

CoRR, April, 2025

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback.

Thai Quoc Hoang, Kung-Hsiang Huang, Shirley Kokane, Jianguo Zhang, Zuxin Liu, Ming Zhu, Jake Grigsby, Tian Lan, Michael S. Ryoo, Chien-Sheng Wu, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong, Juan Carlos Niebles

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers.

Jake Grigsby, Justin Sasek, Samyak Parajuli, Daniel Adebi, Amy Zhang, Yuke Zhu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Launchpad: Learning to Schedule Using Offline and Online RL Methods.

Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi

Proceedings of the Job Scheduling Strategies for Parallel Processing, 2024

AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents.

Jake Grigsby, Linxi Fan, Yuke Zhu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Cross-Episodic Curriculum for Transformer Agents.

Lucy Xiaoyang Shi, Yunfan Jiang, Jake Grigsby, Linxi Fan, Yuke Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PGrad: Learning Principal Gradients For Domain Generalization.

Zhe Wang, Jake Grigsby, Yanjun Qi

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning.

Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi

Proceedings of the Uncertainty in Artificial Intelligence, 2022

RARE: Renewable Energy Aware Resource Management in Datacenters.

Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi

Proceedings of the Job Scheduling Strategies for Parallel Processing, 2022

2021

A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets.

Jake Grigsby, Yanjun Qi

CoRR, 2021

Long-Range Transformers for Dynamic Spatiotemporal Forecasting.

Jake Grigsby, Zhe Wang, Yanjun Qi

CoRR, 2021

Towards Automatic Actor-Critic Solutions to Continuous Control.

Jake Grigsby, Jin Yong Yoo, Yanjun Qi

CoRR, 2021

2020

Measuring Visual Generalization in Continuous Control from Pixels.

Jake Grigsby, Yanjun Qi

CoRR, 2020

TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP.

John X. Morris, Eli Lifland, Jin Yong Yoo, Jake Grigsby, Di Jin, Yanjun Qi

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2020